As of February 2025, English was the most popular language for web content, with over 49.4 percent of websites using it. Spanish ranked second, with six percent of web content, while the content in the German language followed, with 5.6 percent. English as the leading online language United States and India, the countries with the most internet users after China, are also the world's biggest English-speaking markets. The internet user base in both countries combined, as of January 2023, was over a billion individuals. This has led to most of the online information being created in English. Consequently, even those who are not native speakers may use it for convenience. Global internet usage by regions As of October 2024, the number of internet users worldwide was 5.52 billion. In the same period, Northern Europe and North America were leading in terms of internet penetration rates worldwide, with around 97 percent of its populations accessing the internet.

A complete list of live websites using the Network for Good technology, compiled through global website indexing conducted by WebTechSurvey.

As of February 2025, Denmark, Netherlands, Norway, Saudi Arabia, Switzerland and the United Arab Emirates ed the ranking of countries with the highest internet penetration rate, all recording ** percent. The worldwide internet penetration rate as of the same research period was **** percent. Most connected regions According to the most recent observations, Northern Europe ranked first among global regions by connectivity rate. The share of the population accessing the internet in this region was nearly ** percent. Western Europe ranked second, followed by Northern America. Overall, the internet reach was higher than ** percent across all European regions, as well as Northern and Southern Americas. Unconnected populations Despite having the biggest online audiences worldwide, India and China are also the markets with the highest number of individuals not connected to the web. Regarding the share of population without internet access in worldwide markets, North Korea ranks first, as the internet in the country remains blocked for most of the general public as of April 2025. Burundi had **** percent of its population unconnected, followed by Chad, with **** percent.

Code:

Packet_Features_Generator.py & Features.py

To run this code:

pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j

-h, --help show this help message and exit -i TXTFILE input text file -x X Add first X number of total packets as features. -y Y Add first Y number of negative packets as features. -z Z Add first Z number of positive packets as features. -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,... -s S Generate samples using size s. -j

Purpose:

Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.

Uses Features.py to calcualte the features.

startMachineLearning.sh & machineLearning.py

To run this code:

bash startMachineLearning.sh

This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags

Options (to be edited within this file):

--evaluate-only to test 5 fold cross validation accuracy

--test-scaling-normalization to test 6 different combinations of scalers and normalizers

Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use

--grid-search to test the best grid search hyperparameters - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:' - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'

Purpose:

Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.

Data

Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.

Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:

First number is a classification number to denote what website, query, or vr action is taking place.

The remaining numbers in each line denote:

The size of a packet,

and the direction it is traveling.

negative numbers denote incoming packets

positive numbers denote outgoing packets

Figure 4 Data

This data uses specific lines from the Virtual Reality.txt file.

The action 'LongText Search' refers to a user searching for "Saint Basils Cathedral" with text in the Wander app.

The action 'ShortText Search' refers to a user searching for "Mexico" with text in the Wander app.

The .xlsx and .csv file are identical

Each file includes (from right to left):

The origional packet data,

each line of data organized from smallest to largest packet size in order to calculate the mean and standard deviation of each packet capture,

and the final Cumulative Distrubution Function (CDF) caluclation that generated the Figure 4 Graph.

The Easiest Way to Collect Data from the Internet Download anything you see on the internet into spreadsheets within a few clicks using our ready-made web crawlers or a few lines of code using our APIs

We have made it as simple as possible to collect data from websites

Easy to Use Crawlers Amazon Product Details and Pricing Scraper Amazon Product Details and Pricing Scraper Get product information, pricing, FBA, best seller rank, and much more from Amazon.

Google Maps Search Results Google Maps Search Results Get details like place name, phone number, address, website, ratings, and open hours from Google Maps or Google Places search results.

Twitter Scraper Twitter Scraper Get tweets, Twitter handle, content, number of replies, number of retweets, and more. All you need to provide is a URL to a profile, hashtag, or an advance search URL from Twitter.

Amazon Product Reviews and Ratings Amazon Product Reviews and Ratings Get customer reviews for any product on Amazon and get details like product name, brand, reviews and ratings, and more from Amazon.

Google Reviews Scraper Google Reviews Scraper Scrape Google reviews and get details like business or location name, address, review, ratings, and more for business and places.

Walmart Product Details & Pricing Walmart Product Details & Pricing Get the product name, pricing, number of ratings, reviews, product images, URL other product-related data from Walmart.

Amazon Search Results Scraper Amazon Search Results Scraper Get product search rank, pricing, availability, best seller rank, and much more from Amazon.

Amazon Best Sellers Amazon Best Sellers Get the bestseller rank, product name, pricing, number of ratings, rating, product images, and more from any Amazon Bestseller List.

Google Search Scraper Google Search Scraper Scrape Google search results and get details like search rank, paid and organic results, knowledge graph, related search results, and more.

Walmart Product Reviews & Ratings Walmart Product Reviews & Ratings Get customer reviews for any product on Walmart.com and get details like product name, brand, reviews, and ratings.

Scrape Emails and Contact Details Scrape Emails and Contact Details Get emails, addresses, contact numbers, social media links from any website.

Walmart Search Results Scraper Walmart Search Results Scraper Get Product details such as pricing, availability, reviews, ratings, and more from Walmart search results and categories.

Glassdoor Job Listings Glassdoor Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Glassdoor.

Indeed Job Listings Indeed Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Indeed.

LinkedIn Jobs Scraper Premium LinkedIn Jobs Scraper Scrape job listings on LinkedIn and extract job details such as job title, job description, location, company name, number of reviews, and more.

Redfin Scraper Premium Redfin Scraper Scrape real estate listings from Redfin. Extract property details such as address, price, mortgage, redfin estimate, broker name and more.

Yelp Business Details Scraper Yelp Business Details Scraper Scrape business details from Yelp such as phone number, address, website, and more from Yelp search and business details page.

Zillow Scraper Premium Zillow Scraper Scrape real estate listings from Zillow. Extract property details such as address, price, Broker, broker name and more.

Amazon product offers and third party sellers Amazon product offers and third party sellers Get product pricing, delivery details, FBA, seller details, and much more from the Amazon offer listing page.

Realtor Scraper Premium Realtor Scraper Scrape real estate listings from Realtor.com. Extract property details such as Address, Price, Area, Broker and more.

Target Product Details & Pricing Target Product Details & Pricing Get product details from search results and category pages such as pricing, availability, rating, reviews, and 20+ data points from Target.

Trulia Scraper Premium Trulia Scraper Scrape real estate listings from Trulia. Extract property details such as Address, Price, Area, Mortgage and more.

Amazon Customer FAQs Amazon Customer FAQs Get FAQs for any product on Amazon and get details like the question, answer, answered user name, and more.

Yellow Pages Scraper Yellow Pages Scraper Get details like business name, phone number, address, website, ratings, and more from Yellow Pages search results.

An analysis of average internet speeds across U.S. states in 2025, highlighting the fastest and slowest regions.

Countries with the highest speeds demonstrate examples of efficient infrastructure and investment in digital technologies, providing their citizens with fast and stable internet. In contrast, countries with low speeds face numerous challenges, especially economic ones.

Explore the historical Whois records related to best-internet-deals.net (Domain). Get insights into ownership history and changes over time.

Job Offers Web Scraping Search

Targeted Results to Find the Optimal Work Solution

By [source]

About this dataset

This dataset collects job offers from web scraping which are filtered according to specific keywords, locations and times. This data gives users rich and precise search capabilities to uncover the best working solution for them. With the information collected, users can explore options that match with their personal situation, skillset and preferences in terms of location and schedule. The columns provide detailed information around job titles, employer names, locations, time frames as well as other necessary parameters so you can make a smart choice for your next career opportunity

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For more datasets, click here.

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How to use the dataset

This dataset is a great resource for those looking to find an optimal work solution based on keywords, location and time parameters. With this information, users can quickly and easily search through job offers that best fit their needs. Here are some tips on how to use this dataset to its fullest potential:

• Start by identifying what type of job offer you want to find. The keyword column will help you narrow down your search by allowing you to search for job postings that contain the word or phrase you are looking for.

• Next, consider where the job is located – the Location column tells you where in the world each posting is from so make sure it’s somewhere that suits your needs!

• Finally, consider when the position is available – look at the Time frame column which gives an indication of when each posting was made as well as if it’s a full-time/ part-time role or even if it’s a casual/temporary position from day one so make sure it meets your requirements first before applying!

• Additionally, if details such as hours per week or further schedule information are important criteria then there is also info provided under Horari and Temps Oferta columns too! Now that all three criteria have been ticked off - key words, location and time frame - then take a look at Empresa (Company Name) and Nom_Oferta (Post Name) columns too in order to get an idea of who will be employing you should you land the gig!

  All these pieces of data put together should give any motivated individual all they need in order to seek out an optimal work solution - keep hunting good luck!

Research Ideas

• Machine learning can be used to groups job offers in order to facilitate the identification of similarities and differences between them. This could allow users to specifically target their search for a work solution.
• The data can be used to compare job offerings across different areas or types of jobs, enabling users to make better informed decisions in terms of their career options and goals.
• It may also provide an insight into the local job market, enabling companies and employers to identify where there is potential for new opportunities or possible trends that simply may have previously gone unnoticed

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: web_scraping_information_offers.csv | Column name | Description | |:-----------------|:------------------------------------| | Nom_Oferta | Name of the job offer. (String) | | Empresa | Company offering the job. (String) | | Ubicació | Location of the job offer. (String) | | Temps_Oferta | Time of the job offer. (String) | | Horari | Schedule of the job offer. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Explore the historical Whois records related to best-internet-online.com (Domain). Get insights into ownership history and changes over time.

As of March 2025, Singapore had the fastest fixed broadband internet worldwide, with an average download speed of 345.33 Mbps. The UAE ranked second at 313.55 Mbps, while Hong Kong followed in third. Fixed internet connections deliver broadband to a home, office, or other fixed premises, with fiber connections offering the best quality service.

In 2024, Iceland was the worldwide leader in terms of internet freedom. The country ranked first with 94 index points in the Freedom House Index, where each country received a numerical score from 100 (the freest) to 0 (the least free). Estonia ranked second with a 92 index points, followed by Canada, with a score of 86 index points. Internet restrictions worldwide The decline of internet freedom in 2022 is mainly linked to political conflicts in different parts of the world. With the Russian invasion of Ukraine, the Russian government intensified its attempts to control the online content in the country. The government placed restrictions on three different U.S.-based social media platforms at the same time, Twitter, Facebook, and Instagram. These restrictions made it to the top of the longest-lasting limitations on the web in 2022. Social protests rose in Iran following the death of Mahsa Amini in September 2022. The Iranian government decided to shut down the internet and various social media platforms in an attempt to minimize the communication between the protesters. In 2022, 11 new internet restrictions were recorded in Iran. However, residents in the Indian region of Jammu and Kashmir saw the highest number of new internet restrictions, which amounted to more than double than the ones in Iran. The impact of internet shutdowns In 2022, the economic impact of internet restrictions worldwide reached an estimated 23.79 billion U.S. dollars. Meanwhile, the highest financial losses due to internet shutdowns were caused by limitations in Russia, and more than seven thousand hours of restricted various online services had an economic impact of 21.59 billion U.S. dollars. The restrictions impacted around 113 million people in the country. Myanmar placed the most extended restriction on internet services, lasting 17,520 hours in total. Similar restrictions in India affected over 120 million people. 

A fileset to accompany an article in a special issue of Internet Archaeology. In this article, I map the structure of the web to understand the context of archaeological blogging. What is the context of our archaeological blogging? When we blog, are we merely shouting into the void? Do archaeological bloggers link only to one another, and do we shout only to each other (which, it must be admitted, is what our journals and conferences do, too, albeit at slower pace)? Assume a person knows nothing about archaeology: would that person find your blog? Your project website? Your department’s website? Does academic blogging matter? One way to answer these questions is through a mapping of the archaeological web. When a layperson finds a site, she might signal its perceived value through linking, retweeting, commenting, and writing her own blog posts about it. Therefore, various network metrics of this map of the archaeological web can be taken as a kind of proxy for evaluating the impact of our blogging. Given that these blogs are all publicly available (if one knows or can find the address), blogging is a kind of public archaeology- not necessarily an archaeology done for the public, but rather an archaeology done in view of the public. It would be interesting to know if this kind of public archaeology has an impact at all. These signals and linkages in the general noise of the internet are the subject of this paper. In order for us as archaeologists to generate the strongest possible signals on the web, we need to understand the structures that have emerged within the web to best facilitate dissemination. This can help us increase our signals’ visiblity, even though all roads eventually lead to Wikipedia.

As of the first month of 2024, more than nine out of 10 people living in the Bahamas, Costa Rica, Antigua & Barbuda, and Chile were online, putting the countries in the top position regarding internet access in Latin America. Meanwhile, more than 85 percent of the populations of Uruguay, the Dominican Republic, Argentina, Brazil Guyana, and Jamaica were online. On the other hand, less than half of the population of Haiti had access to the internet. Overall, the internet penetration rate in Latin America stood at 74.63 percent. Growth in mobile connectivity… With investments in 4G infrastructure forecast to reach around 211.5 billion U.S. dollars by 2030, the improvement of mobile connectivity is radically changing the picture of access to the internet in Latin America and the Caribbean. One of the best examples is Peru, where the gap between urban and rural areas has greatly diminished in 2021, making its online audiences the fifth largest on the continent in 2023. …at an unequal rate Despite the improvements, Latin America and the Caribbean still face an enormous gap in internet access: the internet penetration rate in the subregion of South America was 80.6 percent in 2023, while only 68.4 percent of people in the Caribbean had access to the web. Despite its investments in mobile connectivity, most of the web traffic in Venezuela still originated from desktop devices in 2023, and only 70.9 Ecuadorians had access to mobile internet in 2023.

This data depicts young adults' reflections on their experiences of social media use during adolescence with the goal of better understanding the effects of social media use on a sample of South African adolescents. The study formed part of a group research project in which several researchers conducted individual studies countrywide on the topic. The goal of the study was to explore and describe young adults’ reflections on their experiences of social media use during adolescence, and the research question for the study was 'what are young adults’ reflections on their experiences of social media use during adolescence?'. The following research methodology was employed, a qualitative research approach; an interpretivist paradigm; the research was regarded as applied research and was guided by an instrumental case study design. The sample was selected by means of snowball and purposive sampling; data was collected by means of a semi-structured interview, with the use of an interview schedule; and thematic analysis was utilised to analyse the data that was obtained. The theoretical framework for this study was Bronfenbrenner’s ecological systems theory. The researcher interviewed 10 participants who fit the specific criteria for inclusion; the sample consisted of young adults living in South Africa, within the geographical area of the City of Tshwane. Participants were between the ages of 19 and 25 and gave an account of their reflections on their social media use between the ages of 11 and 18. Participants were also affected in terms of their biological development (i.e., physical, cognitive, emotional, social, moral as well as their identity development).

Investigate historical ownership changes and registration details by initiating a reverse Whois lookup for the name Best Internet Service Solution.

Explore the historical Whois records related to internet-best-tips.com (Domain). Get insights into ownership history and changes over time.

TagX Web Browsing Clickstream Data: Unveiling Digital Behavior Across North America and EU Unique Insights into Online User Behavior TagX Web Browsing clickstream Data offers an unparalleled window into the digital lives of 1 million users across North America and the European Union. This comprehensive dataset stands out in the market due to its breadth, depth, and stringent compliance with data protection regulations. What Makes Our Data Unique?

Extensive Geographic Coverage: Spanning two major markets, our data provides a holistic view of web browsing patterns in developed economies. Large User Base: With 300K active users, our dataset offers statistically significant insights across various demographics and user segments. GDPR and CCPA Compliance: We prioritize user privacy and data protection, ensuring that our data collection and processing methods adhere to the strictest regulatory standards. Real-time Updates: Our clickstream data is continuously refreshed, providing up-to-the-minute insights into evolving online trends and user behaviors. Granular Data Points: We capture a wide array of metrics, including time spent on websites, click patterns, search queries, and user journey flows.

Data Sourcing: Ethical and Transparent Our web browsing clickstream data is sourced through a network of partnered websites and applications. Users explicitly opt-in to data collection, ensuring transparency and consent. We employ advanced anonymization techniques to protect individual privacy while maintaining the integrity and value of the aggregated data. Key aspects of our data sourcing process include:

Voluntary user participation through clear opt-in mechanisms Regular audits of data collection methods to ensure ongoing compliance Collaboration with privacy experts to implement best practices in data anonymization Continuous monitoring of regulatory landscapes to adapt our processes as needed

Primary Use Cases and Verticals TagX Web Browsing clickstream Data serves a multitude of industries and use cases, including but not limited to:

Digital Marketing and Advertising:

Audience segmentation and targeting Campaign performance optimization Competitor analysis and benchmarking

E-commerce and Retail:

Customer journey mapping Product recommendation enhancements Cart abandonment analysis

Media and Entertainment:

Content consumption trends Audience engagement metrics Cross-platform user behavior analysis

Financial Services:

Risk assessment based on online behavior Fraud detection through anomaly identification Investment trend analysis

Technology and Software:

User experience optimization Feature adoption tracking Competitive intelligence

Market Research and Consulting:

Consumer behavior studies Industry trend analysis Digital transformation strategies

Integration with Broader Data Offering TagX Web Browsing clickstream Data is a cornerstone of our comprehensive digital intelligence suite. It seamlessly integrates with our other data products to provide a 360-degree view of online user behavior:

Social Media Engagement Data: Combine clickstream insights with social media interactions for a holistic understanding of digital footprints. Mobile App Usage Data: Cross-reference web browsing patterns with mobile app usage to map the complete digital journey. Purchase Intent Signals: Enrich clickstream data with purchase intent indicators to power predictive analytics and targeted marketing efforts. Demographic Overlays: Enhance web browsing data with demographic information for more precise audience segmentation and targeting.

By leveraging these complementary datasets, businesses can unlock deeper insights and drive more impactful strategies across their digital initiatives. Data Quality and Scale We pride ourselves on delivering high-quality, reliable data at scale:

Rigorous Data Cleaning: Advanced algorithms filter out bot traffic, VPNs, and other non-human interactions. Regular Quality Checks: Our data science team conducts ongoing audits to ensure data accuracy and consistency. Scalable Infrastructure: Our robust data processing pipeline can handle billions of daily events, ensuring comprehensive coverage. Historical Data Availability: Access up to 24 months of historical data for trend analysis and longitudinal studies. Customizable Data Feeds: Tailor the data delivery to your specific needs, from raw clickstream events to aggregated insights.

Empowering Data-Driven Decision Making In today's digital-first world, understanding online user behavior is crucial for businesses across all sectors. TagX Web Browsing clickstream Data empowers organizations to make informed decisions, optimize their digital strategies, and stay ahead of the competition. Whether you're a marketer looking to refine your targeting, a product manager seeking to enhance user experience, or a researcher exploring digital trends, our cli...

Product review websites are considered an important tool for the marketing of any business In this day of consumerism, most of the people who purchase a product make an informed decision based on what other customers’ experiences are. When it comes to a company's products and services, customer reviews are as important to companies as they are to their customers. One of the ways to get insights on the products of a company is by checking out their product review website to see what other customers have experienced about what they buy. It is no secret that there are some fantastic online review websites on the internet. Some of these websites provide only reviews and testimonials about a variety of products – from restaurants to books to games. While there are many smaller review websites, some of the best are Scamsrapid.com. What Is Scamsrapid.com? Scampsrapid is a website that decides whether the product or a website is legit or fake. What Scamsrapid Aims to Provide You While Scamsrapid was initially set up to expose fraudsters, it soon became clear that the site had a lot of potential for helping good businesses and genuine people improve their services. By talking to these people and getting feedback from all involved parties, Scamsrapid is gradually raising standards across many industries. This has resulted in some great new tools and resources being added to the site. The Motto of Scamsrapid The purpose of it is to provide easy access to resources that help to perform reverse lookups and make decisions about the websites you're visiting - whether they are safe, suspicious, or outright scams. The motto of the website is: "Scams cost the world billions of dollars each year. Let's stop them!" Pros of Scamsrapid Clearly defines the legitimacy of the product or website Always keep an eye on the latest products and websites Product versatility Follows the market trends User-friendly interface Child-friendly content Easy understand Simple to use Supported by a lot of social media platforms like Facebook and Twitter Is Scamsrapid Legit or Hoax? Since the early nineties, scams have been used by people to rip other people off their hard-earned money. Then you can enjoy your free beer with us. Scamsrapid is a totally legit website that helps you to stay away from other scam websites by offering you the most genuine and honest product reviews. You may have heard about scam sites. They might be phishing scams, fake link shorteners, or virus sites. Scamsrapid is here to keep an eye out for you and tell you about scams before they even happen. Final Words Scamsrapid is here to make sure that you don’t get scammed. We know how many scam websites there are on the internet and we deal with it every day. We can’t help but feel frustrated when we do our research and find scam after scam on the internet. The thing that makes us pull our hair out, even more, is that they are almost impossible to avoid.

Dataset

This dataset was created by KhalidMohamed43

Released under Apache 2.0

Contents